code: def _is_max_limit_reached(current: int, maximum: int = -1) -> bool:
      """Check if the limit has been reached (if enabled).
  
      Args:
          current: the current value
          maximum: the maximum value (or -1 to disable limit)
  
      Returns:
          bool: whether the limit has been reached
  
      """
      return maximum != -1 and current >= maximum
  
imports: import inspect
  from contextlib import contextmanager
  from typing import Any, Callable, ContextManager, Generator, Optional, Tuple, Type
  import torch
  import torch.distributed
  from torch import Tensor
  import lightning.pytorch
  from lightning.fabric.utilities.distributed import _distributed_is_initialized
  from lightning.fabric.utilities.imports import _TORCH_EQUAL_2_0, _TORCH_GREATER_EQUAL_1_13
  from lightning.fabric.utilities.warnings import PossibleUserWarning
  from lightning.pytorch.accelerators.xla import XLAAccelerator
  from lightning.pytorch.callbacks.timer import Timer
  from lightning.pytorch.loops import _Loop
  from lightning.pytorch.loops.fetchers import _DataFetcher, _DataLoaderIterDataFetcher, _PrefetchDataFetcher
  from lightning.pytorch.loops.progress import _BaseProgress
  from lightning.pytorch.strategies import FSDPStrategy
  from lightning.pytorch.strategies.parallel import ParallelStrategy
  from lightning.pytorch.strategies.strategy import Strategy
  from lightning.pytorch.trainer.states import RunningStage
  from lightning.pytorch.utilities.rank_zero import rank_zero_warn
  from lightning.pytorch.utilities.signature_utils import is_param_in_hook_signature
label_desc: Use image node_id 4 for calling a global function with example usage: _is_max_limit_reached(current, maximum) and returns: unknown